Source code for span_marker.label_normalizer

import logging
from abc import ABC, abstractmethod
from typing import Any, Dict, Iterator, List, Tuple

from span_marker.configuration import SpanMarkerConfig

logger = logging.getLogger(__name__)

Entity = Tuple[int, int, int]
"""
Tuple of:

* Entity label
* Word start index
* Word end index
"""




class LabelNormalizer(ABC):
    """Class to convert NER training data into a common format used in the :class:`~span_marker.tokenizer.SpanMarkerTokenizer`.

    The common format involves 3-tuples with entity labels, word start indices and word end indices.
    """

    def __init__(self, config: SpanMarkerConfig) -> None:
        super().__init__()
        self.config = config



    @abstractmethod
    def ner_tags_to_entities(self, ner_tags: List[int]) -> Iterator[Entity]:
        pass


    def __call__(self, tokens: List[List[str]], ner_tags: List[List[int]]) -> Dict[str, List[Any]]:
        output = {"ner_tags": [], "entity_count": [], "word_count": []}
        for tokens, ner_tags in zip(tokens, ner_tags):
            ner_tags = list(self.ner_tags_to_entities(ner_tags))
            output["ner_tags"].append(ner_tags)
            output["entity_count"].append(len(ner_tags))
            output["word_count"].append(len(tokens))
        return output





class LabelNormalizerScheme(LabelNormalizer):
    def __init__(self, config: SpanMarkerConfig) -> None:
        super().__init__(config)
        self.label_ids_by_tag = self.config.group_label_ids_by_tag()
        self.start_ids = set()
        self.end_ids = set()



    def ner_tags_to_entities(self, ner_tags: List[int]) -> Iterator[Entity]:
        """Assumes a correct IOB or IOB2 annotation scheme"""
        start_idx = None
        reduced_label_id = None
        for idx, label_id in enumerate(ner_tags):
            # End of an entity
            if start_idx is not None and label_id in self.end_ids:
                yield (reduced_label_id, start_idx, idx)
                start_idx = None

            # Start of an entity
            if start_idx is None and label_id in self.start_ids:
                # compute the schemeless label ID
                reduced_label_id = self.config.id2reduced_id[label_id]
                start_idx = idx

        if start_idx is not None:
            yield (reduced_label_id, start_idx, idx + 1)






class LabelNormalizerIOB(LabelNormalizerScheme):
    def __init__(self, config: SpanMarkerConfig) -> None:
        super().__init__(config)
        # Support for IOB2 and IOB, respectively:
        logger.info("Detected the IOB or IOB2 labeling scheme.")
        self.start_ids = self.label_ids_by_tag["B"] | self.label_ids_by_tag["I"]
        self.end_ids = self.label_ids_by_tag["B"] | self.label_ids_by_tag["O"]





class LabelNormalizerBIOES(LabelNormalizerScheme):
    def __init__(self, config: SpanMarkerConfig) -> None:
        super().__init__(config)
        logger.info("Detected the BIOES labeling scheme.")
        self.start_ids = self.label_ids_by_tag["B"] | self.label_ids_by_tag["S"]
        self.end_ids = self.label_ids_by_tag["B"] | self.label_ids_by_tag["O"] | self.label_ids_by_tag["S"]





class LabelNormalizerBILOU(LabelNormalizerScheme):
    def __init__(self, config: SpanMarkerConfig) -> None:
        super().__init__(config)
        # Support for BILOU and BILO:
        logger.info("Detected the BILOU or BILO labeling scheme.")
        self.start_ids = self.label_ids_by_tag["B"] | self.label_ids_by_tag.get("U", set())
        self.end_ids = self.label_ids_by_tag["B"] | self.label_ids_by_tag["O"] | self.label_ids_by_tag.get("U", set())





class LabelNormalizerNoScheme(LabelNormalizer):
    def __init__(self, config: SpanMarkerConfig) -> None:
        super().__init__(config)
        logger.info("No labeling scheme detected: all label IDs belong to individual entity classes.")



    def ner_tags_to_entities(self, ner_tags: List[int]) -> Iterator[Entity]:
        start_idx = None
        entity_label_id = None
        for idx, label_id in enumerate(ner_tags):
            # End of an entity
            if start_idx is not None and label_id != entity_label_id:
                yield (entity_label_id, start_idx, idx)
                start_idx = None

            # Start of an entity
            if start_idx is None and label_id != self.config.outside_id:
                entity_label_id = label_id
                start_idx = idx

        if start_idx is not None:
            yield (entity_label_id, start_idx, idx + 1)






class AutoLabelNormalizer:
    """Factory class to return the correct LabelNormalizer subclass."""



    @staticmethod
    def from_config(config: SpanMarkerConfig) -> LabelNormalizer:
        if not config.are_labels_schemed():
            return LabelNormalizerNoScheme(config)

        tags = config.get_scheme_tags()
        if tags == set("BIO"):
            return LabelNormalizerIOB(config)
        if tags == set("BIOES"):
            return LabelNormalizerBIOES(config)
        if tags == set("BILOU") or tags == set("BILO"):
            return LabelNormalizerBILOU(config)
        raise ValueError(
            "Data labeling scheme not recognized. Expected either IOB, IOB2, BIOES, BILOU "
            "or no scheme (i.e. one label ID per class, no B-, I- label prefixes, etc.)"
        )